A method, device and equipment for acquiring CDN node distribution and scheduling information

Abstract

The application discloses a CDN node distribution and scheduling information acquisition method, device and equipment, and the method comprises the following steps: obtaining CNAME records and IP addresses to form CNAME-IP binary tuples; the CNAME records and the IP addresses are obtained based on domain name resolution data of a target application or a target website when a CDN server receives a CDN service request sent by a terminal user in a target range; a user geographic position is inferred according to the CNAME-IP binary tuples; a CDN node service provider selected is inferred according to the CNAME-IP binary tuples; a CDN node geographic position, a CDN node traffic volume and a CDN node operator to which the CDN node belongs are inferred according to the CNAME-IP binary tuples; CDN node distribution and scheduling information of the target application or the target website in the target range is obtained according to the user geographic position, the CDN node geographic position, the CDN node traffic volume and the CDN node operator. The method and the device can acquire CDN node distribution and scheduling information based on domain name resolution data, thereby supporting optimization of CDN scheduling service.

Description

Technical Field

[0001] This invention relates to the field of communication network technology, and in particular to a method, apparatus, and device for obtaining CDN node distribution and scheduling information. Background Technology

[0002] As a crucial medium for internet traffic, the node distribution and scheduling of Content Delivery Networks (CDNs) are key factors influencing network operation and development. This situation is determined and controlled by the CDN service providers and content origin sites themselves; other stakeholders in the network and business can only indirectly analyze and infer approximate conditions through network data.

[0003] Existing technologies can typically only analyze a portion of CDN attributes, such as determining the distribution location of CDN nodes or only assessing the coarse scheduling of CDN, without simultaneously obtaining CDN node distribution and scheduling information.

[0004] Of course, CDN node distribution and scheduling information can also be obtained through Deep Packet Inspection (DPI) technology. DPI technology first copies and disassembles user data packets, analyzes the internal information and characteristics of the data packets, identifies packets belonging to the CDN, and then obtains the CDN distribution and scheduling status based on the domain names and IP addresses related to the CDN packets. However, DPI technology is costly and consumes a lot of computing resources, making it unsuitable for long-term, large-scale CDN identification and analysis, and it cannot provide stable and efficient CDN services. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to address the above-mentioned shortcomings of the prior art by proposing a method, apparatus and device for obtaining CDN node distribution and scheduling information. The method and apparatus can obtain both CDN node distribution and CDN node scheduling information, thereby supporting the optimization of CDN scheduling services.

[0006] In a first aspect, the present invention provides a method for obtaining CDN node distribution and scheduling information, the method being applied to a Content Delivery Network (CDN) server, the method comprising the following steps:

[0007] Step S1: Obtain the CNAME record and IP address to form a CNAME-IP tuple; the CNAME record and the IP address are obtained by the CDN server based on the domain name resolution data of the target application or target website when receiving CDN service requests sent by end users within the target range;

[0008] Step S2: Based on the CNAME-IP tuple, infer the user's geographical location; based on the CNAME-IP tuple, infer the selected CDN node service provider; and based on the CNAME-IP tuple, infer the CDN node's geographical location, CDN node's traffic volume, and the CDN node's operator.

[0009] Step S3: Based on the user's geographical location, CDN node geographical location, CDN node traffic volume, and the operator to which the CDN node belongs, obtain the CDN node distribution and scheduling information of the target application or target website within the target range;

[0010] Wherein: the target range is a range preset based on geographical location, the target application is an application that provides services or functions to users, and the target website is a website that provides services or functions to users.

[0011] Furthermore, in step S2, the user's geographical location is inferred based on the CNAME-IP tuple, specifically including:

[0012] The IP address in the CNAME-IP tuple is matched with the IP address location database to infer the user's geographical location;

[0013] In step S2, the selected CDN node service provider is inferred based on the CNAME-IP tuple, specifically including:

[0014] The target domain name is resolved from the CNAME record of the CNAME-IP tuple; the associated CDN node service provider is obtained based on the target domain name.

[0015] Further, in step S2, the geographical location of the CDN node is inferred based on the CNAME-IP tuple, specifically including:

[0016] The CDN node's IP address is obtained from the CNAME-IP tuple, and then the CDN node's IP address is input into the IP location service to obtain the geographical location information of the IP address. By analyzing the switching nodes and router information in the CDN node's network path, the geographical location of the CDN node can be inferred.

[0017] In step S2, the CDN node traffic volume is inferred based on the CNAME-IP tuple, specifically including:

[0018] The CDN node's IP address is obtained from the CNAME-IP tuple. The CDN node's traffic volume is obtained by analyzing the traffic data corresponding to the IP address within a preset time period.

[0019] In step S2, the operator to which the CDN node belongs is inferred based on the CNAME-IP tuple, specifically including:

[0020] The CDN node's IP address is obtained from the CNAME-IP tuple. Based on the IP address, a query is performed to obtain the ISP to which the CDN node belongs.

[0021] Furthermore, in step S3,

[0022] The CDN node distribution information includes the geographical location distribution of CDN nodes;

[0023] The CDN scheduling information includes the user location served by the CDN node and the traffic volume ratio of the CDN node. The traffic volume of the CDN node is determined by NetFlow traffic or DNS resolution request volume information.

[0024] Furthermore, after step S3, step S4 is also included.

[0025] Step S4: Optimize CDN scheduling based on CDN scheduling information.

[0026] Furthermore, in step S4, CDN scheduling is optimized based on CDN scheduling information, including optimizing CDN node location scheduling based on CDN node geographical location. The specific steps are as follows:

[0027] S41: Calculate the distance between the user's location and the geographical location of the selected CDN node to obtain the first distance; and calculate the average distance from all CDN nodes to the user's location to obtain the second distance;

[0028] S42: Compare the first distance and the second distance: If the first distance is greater than the second distance, optimize the CDN scheduling, and select the CDN node from the nearest to the farthest distance according to the distance between the user's location and the CDN node's geographical location during optimization.

[0029] Furthermore, both the first and second distances in step S41 are calculated based on latitude and longitude distances.

[0030] The formula for calculating the first distance is as follows:

[0031]

[0032] L AB Let LA be the distance between points A and B. A LO A The latitude and longitude of point A are respectively, LA B LO B Here, represents the latitude and longitude of point B, and π is the mathematical constant pi.

[0033] The formula for calculating the second distance is as follows:

[0034]

[0035] Where L i Let L be the path distance from the location of the i-th city to the location of the CDN user. i It is calculated based on latitude and longitude distance, k i Let represent the percentage of CDN node service volume in city i out of the total CDN node service volume in all n cities, where n is a natural number greater than 1.

[0036] Secondly, the present invention provides a device for obtaining CDN node distribution and scheduling information, the device being applied to a Content Delivery Network (CDN) server, the device comprising:

[0037] The data acquisition unit is used to acquire CNAME records and IP addresses to form CNAME-IP tuples; both the CNAME record and the IP address are obtained by the CDN server based on the domain name resolution data of the target application or target website when the CDN server receives CDN service requests sent by end users within the target range.

[0038] The inference unit, connected to the data acquisition unit, is used to infer the user's geographical location based on the CNAME-IP tuple; and to infer the selected CDN node service provider based on the CNAME-IP tuple; and to infer the CDN node's geographical location, CDN node's business volume, and the CDN node's operator based on the CNAME-IP tuple.

[0039] The information acquisition unit, connected to the inference unit, is used to obtain the CDN node distribution and scheduling information of the target application or target website within the target range based on the user's geographical location, CDN node geographical location, CDN node traffic volume, and the operator to which the CDN node belongs.

[0040] Wherein: the target range is a range preset based on geographical location, the target application is an application that provides services or functions to users, and the target website is a website that provides services or functions to users.

[0041] Furthermore, the information acquisition unit includes a CDN node distribution information acquisition module and a CDN scheduling information acquisition module, which are connected in parallel.

[0042] The CDN node distribution information acquisition module is used to obtain CDN node distribution information of the target application or target website within the target range based on the user's geographical location, CDN node geographical location, CDN node traffic volume, and the operator to which the CDN node belongs; the CDN node distribution information includes the geographical location distribution of CDN nodes;

[0043] The CDN scheduling information acquisition module is used to obtain CDN scheduling information of the target application or target website within the target range based on the user's geographical location, the CDN node's geographical location, the CDN node's business volume, and the operator to which the CDN node belongs; the CDN scheduling information includes the user's location served by the CDN node and the proportion of the CDN node's business volume.

[0044] Thirdly, the present invention provides an electronic device, which includes the CDN node distribution and scheduling information acquisition device described in the second aspect, and further includes an optimization unit connected to the information acquisition unit, for optimizing CDN scheduling based on CDN scheduling information.

[0045] The beneficial effects of this invention are:

[0046] 1. This invention can obtain complete CDN node distribution and scheduling information based on domain name resolution data, including both CDN node distribution and CDN node scheduling information.

[0047] 2. This invention can further optimize the geographical location service of CDN scheduling service based on the geographical location information in CDN node distribution and scheduling information, thereby improving the reliability and stability of the network.

[0048] 3. Compared with the deep packet inspection (DPI) technology, this invention has lower cost and consumes less computing resources.

[0049] 4. Determine CDN service volume by using NetFlow traffic or DNS resolution request volume information, and combine this with the IP information database to obtain the precise distribution of CDN nodes down to the city level and the size of the service volume.

[0050] 5. Classify the distance between CDN nodes and users into four types, and combine the traffic volume of CDN nodes to calculate the proportion of traffic volume of the four types of nodes, thereby evaluating the distance between CDN nodes and users.

[0051] 6. This invention can estimate the specific distance from a CDN node to a user using latitude, longitude, and network structure.

[0052] 7. Obtaining complete CDN node distribution and scheduling information based on domain name resolution data can improve user experience and reduce operating costs. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the overall process in an embodiment of the present invention;

[0054] Figure 2 This is a schematic diagram of the method for obtaining CDN node distribution and scheduling information in an embodiment of the present invention;

[0055] Figure 3 This is a schematic diagram of the CDN node distribution and scheduling information acquisition device in an embodiment of the present invention;

[0056] In the attached figures, the reference numerals are: 10, data acquisition unit; 20, inference unit; and 30, information acquisition unit. Detailed Implementation

[0057] To enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0058] It is understood that the specific embodiments and accompanying drawings described herein are merely for explaining the invention and are not intended to limit the invention.

[0059] It is understood that, without conflict, the various embodiments and features in the embodiments of the present invention can be combined with each other.

[0060] It is understood that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, while the parts unrelated to the present invention are not shown in the drawings.

[0061] It is understood that each unit or module involved in the embodiments of the present invention may correspond to only one entity structure, or may be composed of multiple entity structures, or multiple units or modules may be integrated into one entity structure.

[0062] It is understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of this invention may occur in a different order than that marked in the accompanying drawings.

[0063] It is understood that the flowcharts and block diagrams of this invention illustrate the possible architecture, functions, and operations of systems, apparatuses, devices, and methods according to various embodiments of this invention. Each block in the flowchart or block diagram may represent a unit, module, program segment, or code, containing executable instructions for implementing the specified function. Furthermore, each block or combination of blocks in the block diagram and flowchart can be implemented using a hardware-based system to achieve the specified function, or using a combination of hardware and computer instructions.

[0064] It is understood that the units and modules involved in the embodiments of the present invention can be implemented by software or by hardware. For example, the units and modules can be located in a processor.

[0065] Example 1:

[0066] like Figure 1 and Figure 2 As shown, this embodiment provides a method for obtaining CDN node distribution and scheduling information. This method is applied to a Content Delivery Network (CDN) server and includes steps S1 to S4:

[0067] Step S1: Obtain the CNAME record and IP address to form a CNAME-IP tuple; both the CNAME record and IP address are obtained by the CDN server based on the domain name resolution data of the target application or target website when receiving CDN service requests sent by end users within the target range.

[0068] Step S2: Based on the CNAME-IP tuple, infer the user's geographical location; based on the CNAME-IP tuple, infer the selected CDN node service provider; and based on the CNAME-IP tuple, infer the CDN node's geographical location, CDN node's traffic volume, and the CDN node's operator.

[0069] As a specific implementation method, step S2, inferring the user's geographical location based on the CNAME-IP tuple, specifically includes:

[0070] The IP address in the CNAME-IP tuple is matched with the IP address location database to infer the user's geographical location;

[0071] In step S2, the selected CDN node service provider is inferred based on the CNAME-IP tuple, specifically including:

[0072] The target domain name is resolved from the CNAME record of the CNAME-IP tuple; the associated CDN node service provider is obtained based on the target domain name.

[0073] In step S2, the geographical location of the CDN node is inferred based on the CNAME-IP tuple, specifically including:

[0074] The CDN node's IP address is obtained from the CNAME-IP tuple, and then the CDN node's IP address is input into the IP location service to obtain the geographical location information of the IP address. By analyzing the switching nodes and router information in the CDN node's network path, the geographical location of the CDN node can be inferred.

[0075] In step S2, the CDN node traffic volume is inferred based on the CNAME-IP tuple, specifically including:

[0076] The CDN node's IP address is obtained from the CNAME-IP tuple. The CDN node's traffic volume is obtained by analyzing the traffic data corresponding to the IP address within a preset time period.

[0077] In step S2, the ISP to which the CDN node belongs is inferred based on the CNAME-IP tuple, specifically including:

[0078] The CDN node's IP address is obtained from the CNAME-IP tuple. Based on the IP address, a query is performed to obtain the ISP to which the CDN node belongs.

[0079] Step S3: Based on the user's geographical location, CDN node geographical location, CDN node traffic volume, and the operator to which the CDN node belongs, obtain the CDN node distribution and scheduling information of the target application or target website within the target range;

[0080] Among them: the target scope is a range preset based on geographical location, the target application is an application that provides services or functions to users, and the target website is a website that provides services or functions to users.

[0081] As one specific implementation method, in step S3,

[0082] The CDN node distribution information includes the geographical location distribution of CDN nodes;

[0083] The CDN scheduling information includes the user location served by the CDN node and the traffic volume ratio of the CDN node. The traffic volume of the CDN node is determined by NetFlow traffic or DNS resolution request volume information.

[0084] Step S4: Optimize CDN scheduling based on CDN scheduling information.

[0085] As a specific implementation method, step S4 optimizes CDN scheduling based on CDN scheduling information, including optimizing CDN node location scheduling based on CDN node geographical location. The specific steps are as follows:

[0086] S41: Calculate the distance between the user's location and the geographical location of the selected CDN node to obtain the first distance; and calculate the average distance from each CDN node to the user's location to obtain the second distance;

[0087] S42: Compare the first distance and the second distance: If the first distance is greater than the second distance, optimize the CDN scheduling, and select the CDN node from the nearest to the farthest distance according to the distance between the user's location and the CDN node's geographical location during optimization.

[0088] Furthermore, both the first and second distances in step S41 are calculated based on latitude and longitude distances.

[0089] The formula for calculating the first distance is as follows:

[0090]

[0091] L AB Let LA be the distance between points A and B. A LO A The latitude and longitude of point A are respectively, LA B LO B Here, represents the latitude and longitude of point B, and π is the mathematical constant pi.

[0092] The formula for calculating the second distance is as follows:

[0093]

[0094] Where L i Let L be the path distance from the location of the i-th city to the location of the CDN user. i It is calculated based on latitude and longitude distance, k i Let represent the percentage of CDN node service volume in city i out of the total CDN node service volume in all n cities, where n is a natural number greater than 1.

[0095] To further clarify this embodiment, as Figure 1 As shown, the implementation process of this embodiment is as follows:

[0096] Step 1: CNAME and IP address statistics

[0097] For the target application or website to be analyzed, manually access its main functions, sections, and content, and at the same time use packet capture software to capture the DNS data packets during the access process.

[0098] Analyze the requested domain name field (excluding the requested CNAME field) in the DNS packets, summarize them by second-level or third-level domains, and select 5-10 of the most frequently occurring domains from the summarized domains as the main origin domains of the target application / website.

[0099] Using the aforementioned domain names as input, search the target local DNS system for all requests and resolution records of these domain names from users using that local DNS within a certain timeframe, such as one day or one week. Domain redirection, i.e., requests and responses that generated CNAME records, are considered as using CDN services. From all the records found, filter out all records that generated CNAME records. Count all CNAME records and their final resolved IP addresses, forming CNAME-IP tuples, and count the number of times each CNAME-IP tuple is resolved.

[0100] In summary, this step, targeting the application or website, extracts the domain name (i.e., CNAME) and IP address used by its CDN to provide services to the target range of users through the DNS system, as well as the mapping relationship between CNAME and IP. This provides foundational data for subsequent analysis.

[0101] Step 2: CDN Node Distribution and Key Attribute Analysis

[0102] a) CDN service provider analysis

[0103] Summarize all CNAME records from Step 1 by second-level domain. Using these second-level domains as input, query the ICP filing database to record the entity to which each second-level domain belongs; this entity can then be considered a CDN service provider. Entities belonging to the same parent company or the same corporate group can be grouped together.

[0104] Based on the CNAME-IP tuple resolution request volume recorded in Part 1, the sum of the resolution request volume for each CNAME second-level domain is calculated, and then the sum of the resolution request volume for each CDN service provider is calculated. This allows analysis of which CDN service providers the target application or website has selected within the target scope and the approximate business volume (resolution request volume) of these CDN service providers.

[0105] b) CDN node distribution and operator analysis

[0106] All IP addresses identified in Step 1 are aggregated into / 24 address ranges if they are IPv4 addresses, and into / 48 address ranges if they are IPv6 addresses. Each IP address range is considered to belong to an independent CDN node.

[0107] Using the aggregated address ranges as input, the IP database is queried to obtain the province, city, and carrier of each IP address range. The province and city of origin indicate the precise geographical location of the CDN node down to the city level, and the carrier of origin indicates the carrier network to which the CDN node is located.

[0108] Using the NetFlow system, we summarize the traffic for each CDN IP address range after this section, with that range as the source address and the target range of user IP addresses as the destination address. This traffic is then used as the service volume for each CDN node. If the NetFlow system is not available, DNS resolution request volume can still be used as an approximate service volume for each CDN node.

[0109] Based on the geographical location and traffic volume of each CDN node, the number of CDN nodes deployed and the traffic volume of the target application or website in each province and city can be determined. This provides a detailed geographical distribution and traffic volume distribution of the CDN nodes serving users within the target area. For the CDN nodes with the highest traffic volume, their specific locations can be further clarified through other means, allowing for targeted monitoring of their access devices and links.

[0110] Based on the carrier and traffic volume of CDN nodes, the number of CDN nodes and traffic volume of the target application or website serving users within the target range across various carriers can be determined. For specific CDN nodes, such as those not belonging to the same carrier network as the target users, their CDN service provider and geographical location can be analyzed in conjunction with other CDN attributes to provide a basis for targeted solutions to cross-network service issues.

[0111] In summary, this step takes the CNAME, IP tuple, and DNS resolution request volume information output from step one as input, and combines them with the ICP filing information database, IP information database, and NetFlow data (if available) to analyze and determine the specific geographical distribution, business volume, CDN service provider, and operator information of the target application or website within the target scope of the CDN. This analysis can further support CDN distribution optimization and key monitoring.

[0112] Step 3: CDN Scheduling Information Analysis

[0113] For CDN nodes and users within the same operator network, if the user range of the Local DNS can be determined (such as a certain province), it can be determined whether the CDN has achieved localized scheduling to serve users by analyzing the distance between the geographical location of the CDN node and the user's location.

[0114] a) Analyze the distance between CDN nodes and users

[0115] Query the network architecture within the target area to obtain the number of network nodes that the path from the city where each CDN node is located to the user's location needs to pass through, and the city where each network node is located.

[0116] The geographical locations of all CDN nodes accessed by Local DNS users are statistically analyzed and categorized into four types: those in the same province as the user, those in a neighboring province and reachable within one hop between provinces, those in a non-neighboring province but reachable within one hop between provinces, and those requiring multiple hops between provinces to reach the user.

[0117] By statistically analyzing the traffic volume of each type of CDN node and the traffic volume of CDN nodes in each province, we can determine the traffic volume of CDN nodes serving users within the target Local DNS range in each province, as well as the proportion of traffic volume for each type of CDN node. If the latter two types of CDN nodes have a high proportion, it can be assumed that there is a large proportion of long-distance CDN services. In this case, we can combine other CDN attributes to analyze the CDN service provider and the province where the CDN is located, providing a basis for targeted solutions to long-distance service scheduling issues.

[0118] By combining statistics from multiple local DNS providers, we can determine the overall CDN scheduling of the target application or website and its chosen CDN service provider within the target area, i.e., which provinces' CDN nodes serve which users in which locations, and what the respective business volume proportions are.

[0119] b) Calculate the average distance from the CDN node to the user

[0120] By querying publicly available latitude and longitude information, we can obtain the latitude and longitude of the city where each CDN node is located, the city where each network node is located, and the approximate latitude and longitude of users within the target range.

[0121] Calculate the distance between two points using the formula based on latitude and longitude:

[0122]

[0123] Where L AB Let LA be the distance between points A and B. A LO A The latitude and longitude of point A are respectively, LA B LO B Here are the latitude and longitude of point B, respectively. 6371.004 is the average radius of the Earth, and 180 / π = 57.2958.

[0124] Based on this, the shortest path from the city where each CDN node is located to the user's location, and the total distance of that path, are calculated.

[0125] Assuming that users of a certain Local DNS access CDN nodes distributed across n cities, the average distance L from these users to the CDN nodes is calculated using the following formula:

[0126]

[0127] Where L iLet k be the path distance from the location of the i-th city to the location of the CDN user. i This represents the percentage of CDN node service volume in city i out of the total CDN node service volume in all n cities.

[0128] This value can serve as a quantitative indicator of the overall distance from this segment of users to the CDN.

[0129] In summary, this step, based on the CDN node location and traffic information from step two, further analyzes the scheduling status of CDN nodes through model classification and formulas, i.e., the distance between their geographical locations and user locations, and can further support the optimization of CDN scheduling services.

[0130] Example 2:

[0131] like Figure 3 As shown, this embodiment provides a device for obtaining CDN node distribution and scheduling information. This device is applied to a Content Delivery Network (CDN) server and includes:

[0132] The data acquisition unit 10 is used to acquire CNAME records and IP addresses to form CNAME-IP tuples. Both CNAME records and IP addresses are obtained by the CDN server based on the domain name resolution data of the target application or target website when the CDN server receives CDN service requests sent by end users within the target range.

[0133] The inference unit 20, connected to the data acquisition unit 10, is used to infer the user's geographical location based on the CNAME-IP tuple; and to infer the selected CDN node service provider based on the CNAME-IP tuple; and to infer the CDN node's geographical location, CDN node's business volume, and the CDN node's operator based on the CNAME-IP tuple.

[0134] The information acquisition unit 30, connected to the inference unit 20, is used to obtain the CDN node distribution and scheduling information of the target application or target website within the target range based on the user's geographical location, CDN node geographical location, CDN node business volume and the operator to which the CDN node belongs.

[0135] Among them: the target scope is a range preset based on geographical location, the target application is an application that provides services or functions to users, and the target website is a website that provides services or functions to users.

[0136] In one specific implementation, the information acquisition unit 30 includes a CDN node distribution information acquisition module and a CDN scheduling information acquisition module, which are connected in parallel.

[0137] The CDN node distribution information acquisition module is used to obtain the CDN node distribution information of the target application or website within the target range based on the user's geographical location, CDN node geographical location, CDN node traffic volume, and the operator to which the CDN node belongs. The CDN node distribution information includes the geographical location distribution of the CDN nodes. The CDN scheduling information acquisition module is used to obtain the CDN scheduling information of the target application or website within the target range based on the user's geographical location, CDN node geographical location, CDN node traffic volume, and the operator to which the CDN node belongs. The CDN scheduling information includes the user location served by the CDN node and the traffic volume ratio of the CDN node.

[0138] Example 3:

[0139] The present invention provides an electronic device, which includes the CDN node distribution and scheduling information acquisition device described in Embodiment 2, and further includes an optimization unit. The optimization unit is connected to the information acquisition unit and is used to optimize CDN scheduling based on CDN scheduling information.

[0140] It is understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for obtaining CDN node distribution and scheduling information, the method being applied to a Content Delivery Network (CDN) server, characterized in that, The method includes the following steps: Obtain the CNAME record and IP address to form a CNAME-IP tuple; both the CNAME record and the IP address are obtained by the CDN server based on the domain name resolution data of the target application or target website when receiving CDN service requests sent by end users within the target range; The user's geographical location can be inferred from the CNAME-IP tuple; And based on the CNAME-IP tuple, the selected CDN node service provider can be inferred; And based on the CNAME-IP tuple, the geographical location of the CDN node, the traffic volume of the CDN node, and the operator to which the CDN node belongs can be inferred; Based on the user's geographical location, CDN node geographical location, CDN node business volume, and the operator to which the CDN node belongs, obtain the CDN node distribution and scheduling information of the target application or target website within the target range; Optimize CDN scheduling based on CDN scheduling information; The optimization of CDN scheduling based on CDN scheduling information includes optimizing CDN node location scheduling based on CDN node geographical location, which specifically includes: The distance between the user's location and the geographical location of the categorized CDN nodes is calculated to obtain the first distance; and the average distance from each CDN node to the user's location is calculated to obtain the second distance; wherein, the second distance is calculated by combining the proportion of the CDN node service volume of the i-th city to the CDN node service volume of all n cities; Compare the first distance and the second distance: if the first distance is greater than the second distance, optimize the CDN scheduling, and select the CDN nodes from the nearest to the farthest geographical location according to the distance between the user's location and the CDN node's geographical location during optimization; Wherein: the target range is a range preset based on geographical location, the target application is an application that provides services or functions to users, and the target website is a website that provides services or functions to users.

2. The method for obtaining CDN node distribution and scheduling information according to claim 1, characterized in that, The process of inferring the user's geographical location based on the CNAME-IP tuple specifically includes: The user's geographical location is inferred by matching the IP address in the CNAME-IP tuple with the IP address location database. The process of inferring the selected CDN node service provider based on the CNAME-IP tuple specifically includes: The target domain name is resolved from the CNAME record of the CNAME-IP tuple; the associated CDN node service provider is obtained based on the target domain name.

3. The method for obtaining CDN node distribution and scheduling information according to claim 1, characterized in that, The process of inferring the geographical location of the CDN node based on the CNAME-IP tuple specifically includes: The CDN node's IP address is obtained from the CNAME-IP tuple. The CDN node's IP address is then input into the IP location service to obtain the geographical location information of the IP address. By analyzing the switching nodes and router information in the CDN node's network path, the geographical location of the CDN node can be inferred. The inference of CDN node traffic based on the CNAME-IP tuple specifically includes: The CDN node's IP address is obtained from the CNAME-IP tuple. The CDN node's traffic volume is obtained by analyzing the traffic data corresponding to the IP address within a preset time period. The process of inferring the ISP of a CDN node based on the CNAME-IP tuple specifically includes: The CDN node's IP address is obtained from the CNAME-IP tuple. Based on the IP address, a query is performed to obtain the ISP to which the CDN node belongs.

4. The method for obtaining CDN node distribution and scheduling information according to claim 1, characterized in that, The CDN scheduling information includes the user location served by the CDN node and the traffic volume ratio of the CDN node; wherein, the traffic volume of the CDN node is determined by NetFlow traffic or DNS resolution request volume information.

5. The method for obtaining CDN node distribution and scheduling information according to claim 1, characterized in that, Before calculating the distance between the user's location and the geographical location of the categorized CDN node, the method further includes: The geographical locations of all CDN nodes accessed by Local DNS users are statistically analyzed and categorized into four types: CDN nodes in the same province as the user, CDN nodes in a neighboring province that are reachable within one hop between provinces, CDN nodes in a non-neighboring province that are reachable within one hop between provinces, and CDN nodes that require multiple hops between provinces to reach the user.

6. The method for obtaining CDN node distribution and scheduling information according to claim 1, characterized in that, Both the first distance and the second distance are calculated based on latitude and longitude. The formula for calculating the first distance is as follows: Let A be the distance between points A and B. , These are the latitude and longitude of point A, respectively. , These are the latitude and longitude of point B, respectively. Pi; The formula for calculating the second distance is as follows: in Let be the path distance from the location of the i-th city to the location of the CDN user. It is calculated based on latitude and longitude distance. Let represent the percentage of CDN node service volume in city i out of the total CDN node service volume in all n cities, where n is a natural number greater than 1.

7. A device for acquiring CDN node distribution and scheduling information, the device being applied to a Content Delivery Network (CDN) server, characterized in that, The device includes: The data acquisition unit is used to acquire CNAME records and IP addresses to form CNAME-IP tuples; both the CNAME record and the IP address are obtained by the CDN server based on the domain name resolution data of the target application or target website when the CDN server receives CDN service requests sent by end users within the target range. The inference unit, connected to the data acquisition unit, is used to infer the user's geographical location based on the CNAME-IP tuple; and to infer the selected CDN node service provider based on the CNAME-IP tuple; and to infer the CDN node's geographical location, CDN node's business volume, and the CDN node's operator based on the CNAME-IP tuple. The information acquisition unit, connected to the inference unit, is used to obtain the CDN node distribution and scheduling information of the target application or target website within the target range based on the user's geographical location, CDN node geographical location, CDN node business volume, and the operator to which the CDN node belongs, so as to optimize CDN scheduling based on the CDN scheduling information. The optimization of CDN scheduling based on CDN scheduling information includes optimizing CDN node location scheduling based on CDN node geographical location, which specifically includes: The distance between the user's location and the geographical location of the categorized CDN nodes is calculated to obtain the first distance; and the average distance from each CDN node to the user's location is calculated to obtain the second distance; wherein, the second distance is calculated by combining the proportion of the CDN node service volume of the i-th city to the CDN node service volume of all n cities; Compare the first distance and the second distance: if the first distance is greater than the second distance, optimize the CDN scheduling, and select the CDN nodes from the nearest to the farthest geographical location according to the distance between the user's location and the CDN node's geographical location during optimization; Wherein: the target range is a range preset based on geographical location, the target application is an application that provides services or functions to users, and the target website is a website that provides services or functions to users.

8. The device for acquiring CDN node distribution and scheduling information according to claim 7, characterized in that, The information acquisition unit includes a CDN node distribution information acquisition module and a CDN scheduling information acquisition module, which are connected in parallel. The CDN node distribution information acquisition module is used to obtain the CDN node distribution information of the target application or target website within the target range based on the user's geographical location, the CDN node's geographical location, the CDN node's business volume, and the operator to which the CDN node belongs. The CDN node distribution information includes the geographical location distribution of CDN nodes; The CDN scheduling information acquisition module is used to obtain CDN scheduling information of the target application or target website within the target range based on the user's geographical location, the CDN node's geographical location, the CDN node's business volume, and the operator to which the CDN node belongs. The CDN scheduling information includes the user location served by the CDN node and the proportion of traffic handled by the CDN node.

9. An electronic device, characterized in that, The electronic device includes the CDN node distribution and scheduling information acquisition device as described in claim 7 or 8, and further includes an optimization unit connected to the information acquisition unit, used to optimize CDN scheduling based on CDN scheduling information.

Images